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<table width="100%" summary="page for S.capricornutum"><tr><td>S.capricornutum</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Effect of cadmium on growth of green alga</h2>

<h3>Description</h3>

<p>Green alga (<em>Selenastrum capricornutum</em>) was exposed to cadmium chloride concentrations
ranging from 5 to 80 micro g/L in geometric progression in 4-day population growth test.
</p>


<h3>Usage</h3>

<pre>data(S.capricornutum)</pre>


<h3>Format</h3>

<p>A data frame with 18 observations on the following 2 variables.
</p>

<dl>
<dt><code>conc</code></dt><dd><p>a numeric vector of cadmium chloride concentrations (micro g/L)</p>
</dd>
<dt><code>count</code></dt><dd><p>a numeric vector of algal counts (10000 x cells /ml)</p>
</dd>
</dl>



<h3>Details</h3>

<p>The data are analysed in Bruce and Versteeg (1992) using a log-normal 
dose-response model (using the logarithm with base 10).
</p>


<h3>Source</h3>

<p>Bruce, R. D. and Versteeg, D. J. (1992) A statistical procedure for modeling continuous toxicity data,
<em>Environ. Toxicol. Chem.</em>, <b>11</b>, 1485&ndash;1494.
</p>


<h3>Examples</h3>

<pre>

## Fitting 3-parameter log-normal model
s.cap.m1 &lt;- drm(count ~ conc, data = S.capricornutum, fct = LN.3())

## Residual plot
plot(fitted(s.cap.m1), residuals(s.cap.m1))

## Fitting model with transform-both-sides approach
s.cap.m2 &lt;- boxcox(s.cap.m1, method = "anova")
summary(s.cap.m2)

## Residual plot after transformation (looks better)
plot(fitted(s.cap.m2), residuals(s.cap.m2))

## Calculating ED values on log scale
ED(s.cap.m2, c(10, 20, 50), interval="delta")

## Fitting model with ED50 as parameter
## (for comparison)
s.cap.m3 &lt;- drm(count ~ conc, data = S.capricornutum, fct = LN.3(loge=TRUE))
s.cap.m4 &lt;- boxcox(s.cap.m3, method = "anova")
summary(s.cap.m4)
ED(s.cap.m4, c(10, 20, 50), interval = "fls")

</pre>


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